Of 60 answers

The most named companies in the study, and S&P 500 financials, with how many of their 60 AI answers named them.

Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder
Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
887 of 2,219
its rank by overall score
Closing balance

Named in

1of 60 answers

by 1 of 4 assistants

Statement note

What this means for Gradient Labs

AI assistants rarely name this fintech infrastructure company, mentioning it in 1 out of 60 answers. In comparison, the typical company in its sector is named in 1.7% of answers as well. Its overall score is 30 out of 100, placing it 887th of 2,219 in the study. The website passes 6 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Gradient Labs by name. AI assistants named it in 1 of the 60 answers. Counting only how often it is named, it ranks 267th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its peers.

Overall score
30Overall score
  • Visibility5
  • Citations3
  • Sentiment50
  • Site quality80
  • AI readiness43
Summary of account
Named by AI in
1.7%
1 of 60 answers
Share of mentions
20.0%
of the mentions of it and its 5 peers
AI readiness
6/14
technical checks passed. Typical for its sector: 4
Rank in its sector
253 of 574
by overall score, where the typical financial technology and data company scores 29

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Line itemsSection 01

Every question, and where the company came up

Gradient Labs came up on 1 of 15 questions. Open any window to read that answer.

  1. 01What should I look for when choosing an AI-powered platform for lending and collections automation?0/4
  2. 02Is investing in AI-driven customer operations automation worth it for mid-sized financial institutions?0/4
  3. 03Why might an AI agent in a financial services workflow struggle with resolving complex disputes?0/4
  4. 04AI agents vs. rule-based bots for disputes and KYC processes in financial services—what's the difference?0/4
  5. 05How can I address accuracy issues when automating KYC with AI platforms?0/4
  6. 06Which AI automation solutions are most effective at reducing manual work in financial institution back offices?0/4
  7. 07What pricing models are common for AI customer operations platforms in the financial sector?0/4
  8. 08How can automated AI agents streamline customer onboarding in banks and credit unions?0/4
  9. 09What are common applications of AI automation for collections and secure promise to pay workflows?0/4
  10. 10Alternatives to using AI agents for managing lending and customer support operations?0/4
  11. 11How do AI-powered customer support tools compare to traditional automation for handling financial service operations?0/4
  12. 12How can AI agents improve back-office workflows in banking and credit unions?0/4
  13. 13What are the best AI platforms for automating customer operations in financial services?1/4
  14. 14How much does it typically cost to implement AI automation for customer support and back-office tasks in financial services?0/4
  15. 15What are some non-AI alternatives for automating customer operations in the banking sector?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 1/15All assistants: 1/60
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. Across the study, on 50% of the questions where a company is named, only one AI assistant names it.

Transaction detailSection 02

What Gemini actually said

An answer that names the company

Gemininamed the company

“What are the best AI platforms for automating customer operations in financial services?”

… Gradient Labs: Strong for financial-services operations and disputes, including evidence gathering and audit logs.

Sierra: Designed for enterprise service across channels, providing connected customer context and configurable agents.

Kore.ai: Excellent for banks connecting voice and digital service to core systems, offering banking workflows and API integration.

Cognigy: A good choice for voice and digital automation in a contact center, enabling banking self-service and agent assistance.

Boost.ai: Helps businesses automate customer service an

The AI’s answer as we received it, shortened and not checked for accuracy.

PayeesSection 03

Where the mentions went

The companies these answers named, and how the mentions were split between this company and its peers.

Also named

CompanyTimes named
  1. 01
    Cognigy
    2
  2. 02
    Kasisto
    1

Share of mentions

CompanyShare
  1. Cognigy
    60.0%
  2. Gradient Labs
    20.0%
  3. Kasisto
    20.0%
  4. Inscribe AI
    0.0%
  5. Unit21
    0.0%
  6. Agent IQ
    0.0%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    fin.ai
    18
  2. 02
    gradient-labs.ai (its own website)
    8
  3. 03
    creatio.com
    8
  4. 04
    kognitos.com
    7
  5. 05
    mckinsey.com
    6
  6. 06
    usefini.com
    4
  7. 07
    assistents.ai
    4
  8. 08
    kore.ai
    3
  9. 09
    lendflow.com
    3
  10. 10
    lorikeetcx.ai
    3

Gradient Labs is in the study as a fintech infrastructure company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
1/15
Claude
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How Gradient Labs compares with all 2,219 companies

Every tower is a company in the study, taller for a higher overall score and lit where AI assistants named it. Its own group stays lit. Hover a tower to see it, and click to open it.

What makes up the score

Each part is scored out of 100.

Visibility
5

How often AI assistants name the company, and how that compares with its peers

Citations
3

How often AI uses the company's own website as a source

Sentiment
50

How positively AI describes the company

Site quality
80

How well built the website's own pages are

AI readiness
43

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Against its sectorSection 07

Compared with financial technology and data companies

574 companies in this sector. The gold tick on each bar is the typical company.

Overall score
30
Ranks 253 of 574. Typical company: 29
Named in answers
1.7%
Ranks 267 of 574. Typical company: 1.7%
AI readiness
43
Ranks 29 of 574. Typical company: 29
Against its categorySection 08

Compared with fintech infrastructure companies

315 companies in this category. The gold tick on each bar is the typical company.

Overall score
30
Ranks 117 of 315. Typical company: 28
Named in answers
1.7%
Ranks 123 of 315. Typical company: 1.7%
AI readiness
43
Ranks 17 of 315. Typical company: 29
AI agentsSection 09

Ready for AI agents

What this website publishes for an AI agent to read, use and pay through, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals
Can an AI agent check out here?

Not by itself. Gradient Labs publishes none of the agent payment protocols we look for. An agent would have to click through the website like a person.

Agent payment protocols
  • x402Not present
  • MPPNot present
  • AP2Not present
  • ACPNot present
  • UCPNot present
Interfaces for AI agents
  • MCP Server CardNot present
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogNot present
  • llms.txtPublished
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 86.1%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 87.9%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 1.5%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 4.3%
Content accessibility
100 of 100
  • Markdown negotiationPassed

    Requests sent with Accept: text/markdown receive a markdown version of the page.

    study: 6.2%
  • llms.txtPassed

    An llms.txt that tells language models what the site offers.

    study: 31.0%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 92.7%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 2.3%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.3%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 5.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.2%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.8%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.2%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 1.0%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 0.0%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.2%

Score 47 of 100 · 97% of checks could run · checked on October 9, 2026 · gradient-labs.ai · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 10

The checks behind the AI readiness score

6 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.

These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.

Show the 14 checks

Discoverability

  • Passedrobots.txt publishedstudy: 85.1%
  • PassedXML sitemapstudy: 79.4%
  • PassedHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • PassedMarkdown content negotiationstudy: 7.4%
  • Passedllms.txt publishedstudy: 28.1%
  • PassedToken budget (page weight)study: 97.3%

Bot Access Control

  • Not metExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • Not metOAuth Authorization Server discoverystudy: 5.2%
  • Not metOAuth Protected Resource discoverystudy: 4.6%
  • Not metMCP Server Cardstudy: 0.2%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 0.3%
  • Not metAgent Skills declaredstudy: 0.1%
AI crawlersSection 11

What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 86% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI

  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBotallowed
  • Diffbotallowed
  • Omgilibotallowed

AI search

  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBotallowed

Answering questions

  • ChatGPT-Userallowed
  • Claude-Userallowed
  • Perplexity-Userallowed
  • DuckAssistBotallowed
  • MistralAI-Userallowed

Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.

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